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Network switches - What you should know

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/Network switches - What you should know

Switches are an essential part of computer networks, providing a way of connecting devices together to allow communication between them. A switch is a network device that connects devices on a local area network (LAN) to allow them to communicate with each other. Switches operate at the data link layer of the OSI model, which is the second layer of the seven-layer model. This layer is responsible for the reliable transfer of data between network devices.

Basic informations

Switches come in different types and configurations, with varying capabilities and performance characteristics. The most common types are:

  • Unmanaged Switches – these switches are the simplest type and are typically used in small networks. They provide basic connectivity between devices and cannot be configured.
  • Managed Switches – these devices offer more advanced features such as VLANs (Virtual Local Area Networks), QoS (Quality of Service) and port mirroring.
  • Layer 3 switches – these switches are also known as routing switches because they can route traffic between different subnets or VLANs. They are more expensive than other types of these devices, but are essential in larger networks.

Switches can be further classified based on their architecture, such as:

  • Modular Switches – these switches allow more ports or features to be added by adding modules to the switch.
  • Fixed Switches – urządzenia te są dostarczane z ustaloną liczbą portów i funkcji, których nie można zmienić ani uaktualnić.
  • Stackable Switches – these devices come with a fixed number of ports and features that cannot be changed or upgraded.

Switches use a variety of technologies to enable communication between devices, such as:

  • The most common technology used in switches is Ethernet. This is a set of standards for transmitting data over a LAN.
  • Spanning Tree Protocol (STP) is a protocol used in switches to prevent loops in the network. It works by disabling redundant links between switches, ensuring that there is only one active path between any two devices.
  • Virtual Local Area Networks (VLANs). VLANs enable the creation of logical networks within a physical network. This provides security and performance benefits by distributing traffic between different groups of devices.
  • When it comes to choosing a network switch for an organisation, there are several factors to consider, including performance, scalability, reliability and cost. The three main players in the switch market are Cisco, Dell & IBM. Let's take a closer look at each of these companies and their characteristics.

Cisco

Cisco is a dominant player in the networking industry and offers a wide range of switch models designed for businesses of all sizes. Their switches are known for their high performance, reliability and advanced features such as virtualisation and security.

One of Cisco's flagship switch models is the Catalyst series, which offers a range of options for different network sizes and requirements. Catalyst switches are designed for data centre, campus and branch office environments and can support up to 10Gbps per port. Catalyst switches are also equipped with advanced security features such as access control lists (ACLs), port security and MAC address filtering.

Another popular Cisco switch series is the Nexus series, which is designed for high-performance data centre environments. Nexus switches can support up to 40Gbps per port and offer advanced features such as virtualisation, storage networking and high availability.

Dell

Dell is another big player in the switch market, offering a range of switch models for small and medium-sized businesses. Dell switches are known for their ease of use, affordability and scalability.

One of Dell's popular switch ranges is the PowerConnect series, which offers a range of options for different network sizes and requirements. PowerConnect devices are designed for small and medium-sized businesses and can support up to 10Gbps per port. PowerConnect switches are also equipped with advanced features such as VLAN support, link aggregation and QoS.

Another popular Dell switch series is the N-Series, which is designed for high-performance data centre environments. The N-series switches can support up to 40Gbps per port and offer advanced features such as virtualisation, storage networking and high availability.

IBM

IBM is also a major player in the switch market, offering a range of enterprise-level switch models. IBM switches are known for their advanced features, high performance and reliability.

One of IBM's flagship switch models is the System Networking RackSwitch series, which offers a range of options for networks of different sizes and requirements. RackSwitches are designed for data centre environments and can support up to 40Gbps per port. RackSwitch devices are also equipped with advanced features such as virtualisation, storage networking and high availability.

Another popular IBM switch series is the System Networking SAN series, which is designed for storage area network (SAN) environments. Such switches can support up to 16Gbps per port and offer advanced features such as Fabric Vision technology, which provides real-time visibility and monitoring of this environment.

Summary

Overall, each of these switch manufacturers offers a range of models to meet the needs of businesses of different sizes and requirements. When selecting such a device, factors such as performance, scalability, reliability and cost should be considered, as well as the specific features and capabilities offered by each switch model.

What is Cybersecurity?

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/What is Cybersecurity?

The rapid pace of technological progress has brought unprecedented opportunities for innovation, communication and efficiency. However, as dependence on technology increases, so does the risk of cyber attacks. Cyber security has become one of the most pressing issues of our time, affecting individuals, companies and governments around the world. The consequences of cyber attacks can range from financial losses to disruption of critical infrastructure and even loss of human life.

In recent years, we have witnessed a number of high-profile cyber attacks, including the WannaCry ransomware attack that affected hundreds of thousands of computers worldwide, the Equifax data breach that exposed the confidential information of millions of people, and the SolarWinds supply chain attack that involved many government agencies and private companies. These incidents underscore the seriousness of the cyber threat situation and the need for effective cybersecurity measures.

The current state of cybersecurity

Despite significant efforts to improve network security, the current state of cybersecurity remains precarious. Cyber attacks are becoming more sophisticated, more frequent and have a growing impact. Cybercriminals are constantly developing new attack methods and exploiting vulnerabilities in software and hardware systems.

Moreover, the COVID-19 pandemic has created new opportunities for cyber attacks. With the rapid shift to remote work and online services, organizations are more vulnerable than ever to cyber attacks. Phishing attacks, ransomware attacks and other forms of cyber attacks have increased during the pandemic.

The most common cyber threats

There are many cyber risks that individuals, companies and governments should be aware of. Here are the most common risks involved:

  • Malware – is a type of malware that is designed to damage computer systems or steal sensitive information. Typical types of malware are viruses or Trojans.
  • Ransomware – is a type of malware that is designed to extort money by blocking access to files or a computer system until a ransom is paid.
  • Phishing – is a type of social engineering attack in which cybercriminals use emails, phone calls or text messages to trick people into divulging sensitive information or clicking on a malicious link.
  • DDoS attacks (Distributed Denial of Service) – involve flooding a site or server with traffic, causing it to crash and make it unavailable to users.
  • „man-in-the-middle” attacks – these occur when an attacker intercepts and alters communications between two parties in order to steal sensitive information or inject malicious code.
  • Zero-day exploits – are vulnerabilities in software or hardware that are unknown to the manufacturer and therefore not patched. Cybercriminals can exploit these vulnerabilities to gain unauthorized access to systems or data.

Cybersecurity challenges

There are several challenges we face in achieving effective cyber security. One of the primary challenges is the shortage of qualified cyber security professionals. This industry is experiencing a significant shortage of qualified professionals, making it difficult for organizations to find and hire qualified experts to protect their systems.

Another challenge is the complexity of modern technology systems. With the proliferation of IoT ("Internet of Things") devices, cloud computing and other emerging technologies, the attack surface has increased significantly, and this makes it more difficult to detect and respond to cyber attacks.

Emerging technologies and strategies

Despite these challenges, there are new technologies and strategies that offer hope for a more secure future. For example, artificial intelligence (AI) and machine learning (ML) can be used to detect and respond to cyber threats in real time. Blockchain technology has the potential to increase data security and privacy, while quantum computing may enable us to develop more secure encryption methods.

In addition, organizations are taking a more proactive approach to cyber security. This includes implementing security measures such as multi-factor authentication, training and awareness programs for employees, and continuous monitoring and testing of systems.

Summary

In conclusion, cyber security is a critical issue that affects all aspects of our lives. Cyber attacks have the potential to cause significant damage. However, there are new technologies and strategies that offer hope for a safer future. By working together, we can overcome cybersecurity challenges and build a safer, more protected digital world.

Artificial intelligence - Significant help or threat?

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/Artificial intelligence - Significant help or threat?

Artificial Intelligence (AI) is a rapidly developing technology that is changing the way we live and work. From virtual assistants and chatbots to cars that drive themselves and analyze the traffic situation and smart homes, AI is already having a significant impact on our daily lives, and sometimes we don't even realize it. In this article, we will explore the development of AI, the emergence of GPT chatbots, and the opportunities and risks posed by this technology.

Development of artificial intelligence

AI has been in development for decades, but recent advances in machine learning and deep learning have greatly accelerated its progress. Machine learning is a type of artificial intelligence that allows computers to learn from data without explicit programming. Deep learning is a subset of machine learning that uses artificial neural networks to simulate the way the human brain works.

As a result of these advances, AI is now capable of performing tasks once thought impossible, such as image recognition and natural language processing. These capabilities have opened up a wide range of new applications for AI, from healthcare and finance to transportation and entertainment.

Chat GPT

One of the most exciting developments related to artificial intelligence is the emergence of the GPT chatbot. This acronym stands for "Generative Pre-trained Transformer," a type of AI model that can generate human-like responses to questions we ask it. This technology has been used to create chatbots that can talk to users in a natural and engaging way, just as if we were writing with a human. GPT chat has many potential applications, from customer service and sales to mental health support and education. It can also be used to create virtual companions or assistants that could provide emotional support or help with daily tasks.

Threats posed by the development of artificial intelligence

The development of artificial intelligence has the potential to revolutionize many areas of our lives, but it also poses significant risks. Here are some of the key risks posed by AI development:

  • Loss of jobs and reorganization of professions – as AI becomes more capable, it could replace many jobs that are currently performed by humans. This could lead to widespread unemployment and economic disruption, especially in industries that rely heavily on manual labor or routine tasks.
  • Bias and discrimination – AI algorithms are only as unbiased as the data they are trained on. If the data is biased or incomplete, the algorithm can produce biased or discriminatory results. This can lead to unfair treatment of individuals or groups, especially in areas such as hiring, lending and criminal justice.
  • Threats to security and privacy – As artificial intelligence becomes more ubiquitous, it also becomes a more attractive target for cyberattacks. AI systems can also be used to launch cyber attacks, such as phishing or social engineering attacks. In addition, AI systems can collect and analyze huge amounts of personal data, raising concerns about privacy and data security.
  • Autonomous weapons – AI technology can be used to create autonomous weapons that can make decisions about who to target and when. This could lead to an arms race in which countries seek to develop increasingly sophisticated AI-powered weapons, potentially leading to a catastrophic conflict.
  • Existential risk – Some experts have expressed concern about the possibility of a "technological singularity" in which AI becomes so powerful that it surpasses human intelligence and becomes impossible to control. This could lead to a number of disastrous consequences, such as the complete subjugation of humanity or the extinction of the human race.

Opportunities arising from AI development

The development of AI offers many potential opportunities in many fields. Here are some of the key opportunities that may arise from the continued development of AI:

  • Improvement of efficiency and productivity – AI has the potential to automate many tasks that are currently done manually, leading to increased efficiency and productivity. This can lead to lower costs and higher profits for businesses, as well as more free time for people who previously performed the task manually.
  • Improved decision-making – Artificial intelligence can process massive amounts of data and make predictions and recommendations based on that data. This can help individuals and organizations make more informed decisions, especially in areas such as healthcare, finance and transportation.
  • Personalization and customization – AI can be used to analyze data about individuals and personalize products and services based on their preferences and needs. This can lead to better customer experiences and increased loyalty.
  • faster development in the medical field –  Artificial intelligence can be used to analyze medical data and identify patterns and trends that could lead to more accurate diagnoses and more effective treatments. AI-powered medical devices could also help monitor and treat patients more effectively.
  • Environmental sustainability – AI can be used to optimize energy consumption, reduce waste and improve resource allocation, leading to a more sustainable future.
  • Scientific discoveries – Artificial intelligence can be used to analyze large data sets and identify patterns that can lead to new scientific discoveries and breakthroughs.
  • Enhanced safety and security – AI can be used to detect and prevent cyber attacks, improve public safety and help law enforcement agencies identify and apprehend criminals.

Summary

Artificial Intelligence (AI) is a rapidly developing technology that is changing the world in many ways. The emergence of GPT chatbots is just one example of AI's incredible potential. However, it also poses some significant risks, such as the potential impact on jobs and the risk of misuse. It is important to continue to develop AI responsibly and to carefully consider the opportunities and risks that the technology presents.

What is Edge Computing?

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/What is Edge Computing?

The development of edge computing technology has revolutionized the way we think about data processing and storage. With the growing demand for faster and more efficient access to data and applications, edge computing has emerged as a savior of sorts. In this article, we will explore the concept of this technology in the context of servers, including its definition, history and applications. We will also discuss the features, advantages and disadvantages of this solution in servers and the latest trends and technologies in this field.

Edge Computing. What is it?

Edge computing is a distributed processing model that brings data processing and storage closer to where it is needed to reduce latency and increase efficiency. This concept was first introduced in 2014 and has since gained popularity due to the growth of the Internet of Things (IoT) and the need for real-time data processing.

History behind it

Its origins can be traced to the concept of distributed computing, which dates back to the 1970s. However, the specific term "edge computing" was coined in 2014 by Cisco, which recognized the need for a new computing model to handle the growing number of IoT devices.

How does it work?

Edge computing involves deploying small low-powered computers, known as edge devices, at the edge of the network, closer to where the data is generated. These edge devices process and store data locally, and send only the most relevant data to the cloud for further processing and storage. This reduces the amount of data that must be sent to the cloud, thereby reducing latency and improving response time.

Edge computing in the context of servers

Edge computing is increasingly being applied to servers, especially in the context of edge data centers. Edge data centers are smaller data centers that are located closer to end users to provide faster access to data and applications. By deploying edge servers in these locations, enterprises can improve the performance of their applications and reduce latency.

Server aiming features

Edge computing in servers offers a number of key features, including:

  • Low latency – processing data locally, edge servers can provide users with real-time responses.
  • Scalability – edge servers can be easily scaled up or down as needed, allowing companies to respond quickly to changes in demand.
  • Safety – by processing data locally, edge computing helps improve data security and privacy, as sensitive data does not need to be transmitted over the network.
  • Cost effectiveness – by reducing the amount of data that must be sent to the cloud, edge computing can help reduce the cost of cloud storage and processing.

Advantages of edge computing in servers

Edge computing in servers offers a number of benefits to enterprises, including:

  • Improving performance – By reducing latency and improving response time, edge computing can help companies deliver faster and more responsive applications.
  • Improved reliability – Processing data locally, edge servers can help ensure that applications remain operational even if connectivity to the cloud is lost.
  • Greater flexibility – By deploying edge servers, companies can choose to process data locally or in the cloud, depending on their specific needs.
  • Enhanced security – By processing data locally, edge computing can help improve data security and privacy.

Disadvantages of edge computing in servers

While edge computing in servers offers many benefits, there are also some potential drawbacks to consider. These include:

  • Increased complexity – Deploying edge servers requires careful planning and management, and can add complexity to the overall IT infrastructure.
  • Higher costs – Deploying edge computing can be more expensive than relying solely on cloud infrastructure, due to the need to purchase and maintain additional hardware.
  • Limited processing power – Edge servers may have limited processing power compared to cloud servers, which may affect their ability to handle large amounts of data.

Summary

Edge computing is a powerful technology that can help businesses improve the performance, reliability and security of their applications. By deploying edge servers, companies can enjoy the benefits of edge computing while taking advantage of the scalability and cost-effectiveness of cloud computing. However, it is important to carefully consider the potential advantages and disadvantages of edge computing before deciding to implement it.

HPE FRONTIER - The world's most powerful supercomputer.

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/HPE FRONTIER - The world's most powerful supercomputer.

The Hewlett Packard Enterprise (HPE) Frontier supercomputer is one of the most powerful supercomputers in the world. It was developed in cooperation with the US Department of Energy (DOE) and is located at Oak Ridge National Laboratory in Tennessee, USA. The Frontier supercomputer was designed to help scientists solve the most complex and pressing problems in a variety of fields, including medicine, climate science and energy.

Tech specs

The HPE Frontier supercomputer is built on the HPE Cray EX supercomputer architecture, which consists of a combination of AMD EPYC processors and NVIDIA A100 GPUs. Its peak performance is 1.5 exaflops (one quintillion floating-point operations per second) and can perform more than 50,000 trillion calculations per second. The system has 100 petabytes of storage and can transfer data at up to 4.4 terabytes per second.

Applications

The HPE Frontier supercomputer is used for a wide range of applications, including climate modeling, materials science and astrophysics. It is also being used to develop new drugs and treatments for diseases such as cancer and COVID-19.

Climate modeling

The Frontier supercomputer is being used to improve our understanding of the Earth's climate system and to develop more accurate climate models. This will help scientists predict the impacts of climate change and develop mitigation strategies.

Development of materials

The supercomputer is also being used to model and simulate the behavior of materials at the atomic and molecular levels. This will help scientists develop new materials with unique properties, such as increased strength, durability and conductivity.

Astrophysics

The Frontier supercomputer is being used to simulate the behavior of the universe on a large scale, including the formation of galaxies and the evolution of black holes. This will help scientists better understand the nature of the universe and the forces that govern it.

Medical developments

The supercomputer is being used to simulate the behavior of biological molecules, such as proteins and enzymes, in order to develop new drugs and treatments for diseases. This will help scientists identify new targets for drug development and develop more effective treatments for a wide range of diseases.

Summary

The HPE Frontier supercomputer represents a major step forward in the development of high-performance computing. Its unprecedented computing power and storage capacity make it a valuable tool for researchers in many fields. Its ability to simulate complex systems at a high level of detail helps us better understand the world around us and develop solutions to some of the most pressing challenges facing humanity.

NVIDIA H100 - Revolutionary graphics accelerator for high-performance computing

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/NVIDIA H100 - Revolutionary graphics accelerator for high-performance computing

NVIDIA, a leading graphics processing unit (GPU) manufacturer, has unveiled the NVIDIA h100, a revolutionary GPU gas pedal designed for high-performance computing (HPC). This groundbreaking gas pedal is designed to meet the demands of the most demanding workloads in the fields of artificial intelligence (AI), machine learning (ML), data analytics and more.

How it's built

NVIDIA h100 is a powerful GPU accelerator that is based on NVIDIA's Ampere architecture. It is designed to deliver unparalleled performance for HPC workloads and can support a wide range of applications, from deep learning to scientific simulation. The h100 is built on the NVIDIA A100 Tensor Core GPU, which is one of the most powerful GPUs available on the market today.

Unique features

The NVIDIA h100 is equipped with several features that set it apart from other GPU accelerators on the market. Some of the most notable features are:

  • High performance – The NVIDIA h100 is designed to deliver the highest level of performance for HPC workloads. It features 640 Tensor cores that offer up to 1.6 teraflops of performance in double precision mode and up to 3.2 teraflops of performance in single precision mode.
  • Memory bandwidth – The H100 has 320 GB/s of memory bandwidth, allowing it to easily handle large data sets and complex calculations.
  • NVLink – The H100 also supports NVIDIA's NVLink technology, which enables multiple GPUs to work together as a single unit. This enables faster data transfer and processing between GPUs, which can significantly increase performance in HPC workloads.
  • Scalability – NVIDIA h100 is highly scalable and can be used in a wide variety of HPC applications. It can be deployed in both on-premises and cloud environments, making it a flexible solution for organizations of all sizes.

Comparisson

When comparing the NVIDIA h100 to other GPU gas pedals on the market, there are a few key differences to consider. Here is a brief comparison between the NVIDIA h100 gas pedal and some of its top competitors:

  • NVIDIA H100 vs NVIDIA A100 - The NVIDIA H100 is built on the same architecture as the A100, but has twice the memory bandwidth and is optimized for HPC workloads.
  • NVIDIA H100 vs AMD Instinct MI100 - The H100 outperforms the MI100 in terms of single precision performance, memory bandwidth and power efficiency.
  • NVIDIA H100 vs. Intel Flex 170 – The H100 was designed specifically for HPC workloads, where Intel's Flex series is a more versatile gas pedal having weaker performance (80GB vs. 16GB of memory).

Summary

NVIDIA h100 is a powerful and versatile GPU accelerator that is designed for high-performance computing workloads. Its high performance, memory bandwidth and NVLink support make it an excellent choice for organizations that require superior computing power. Compared to top competitors, the h100 outperforms in HPC optimization and scalability, making it an ultimate accelerator.

Servers and Data Centers

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/Servers and Data Centers

Data centers and servers are the backbone of today's digital world. They store, process and transmit huge amounts of data every day, enabling us to access information, communicate with others and conduct business online. In this article, we will outline the importance of data centers and servers, how they operate, and the challenges and trends shaping their future.

What is a data center?

A data center is a facility used to store computer systems and related components, such as telecommunications and storage systems. Data centers are designed to provide high levels of availability, security and reliability to ensure that stored and processed data is always available and protected.

They come in a variety of sizes, from small server rooms to large corporate facilities that can cover hundreds of square meters. Some data centers are owned and operated by individual organizations, while others are operated by third-party service providers and offer hosting services to multiple customers.

How do the servers work?

Servers are the backbone of data centers, providing the computing power needed to process and store data. A server is a computer system that is designed to provide specific services or resources to other computers or devices connected to a network.

Servers can perform many functions, such as hosting websites, running applications and storing and processing data. A server can be a physical machine or a virtual machine that runs on top of a physical machine. Virtualization technology allows multiple virtual servers to run on a single physical machine, allowing organizations to maximize computing resources and reduce costs.

Challenges and trends

As the demand for digital services continues to grow, data centers and servers face several challenges and trends that will shape their future.

  • One of the primary challenges is the need for greater energy efficiency. Data centers consume huge amounts of energy, and as the number of data centers grows, so does their environmental impact. To meet this challenge, data centers are adopting more energy-efficient technologies, such as advanced cooling systems, and using renewable energy sources such as solar and wind power.
  • Another challenge is the need for greater security. Data breaches can have serious consequences, both for organizations and individuals. Data centers are implementing more stringent security measures, such as multi-factor authentication and encryption, to protect against cyber attacks.
  • In terms of trends, "edge processing" is becoming an important trend in data center and server architecture. It involves processing data closer to the source, reducing latency and improving performance. This is especially important for applications requiring real-time data processing, such as autonomous vehicles and industrial automation.

Summary

Data centers and servers are essential components of the digital infrastructure that supports our modern world. They enable us to access and store vast amounts of information, and provide the computing power needed for critical applications and services. As the demand for digital services continues to grow, data centers and servers will face ongoing challenges and trends that will shape their future. By adopting innovative technologies and strategies, data centers and servers can continue to evolve and meet the needs of our rapidly changing digital world.

Virtual Machine - What Is It and Why Is It So Useful?

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/Virtual Machine - What Is It and Why Is It So Useful?

Many of today's cutting-edge technologies, such as cloud computing, edge computing and microservices, owe their origins to the concept of the virtual machine - the separation of operating systems and software instances from the underlying physical computer.

What is a virtual machine?

A virtual machine (VM) is software that runs programs or applications without being tied to a physical machine. A VM instance on a host computer can run one or more guest machines. Each VM has its own operating system and runs independently of other VMs, even if they are on the same physical host. VMs are typically run on servers, but they can also run on desktop systems and even embedded platforms. Multiple virtual machines can share resources with a physical host, including CPU cycles, network bandwidth and memory.

Virtual machines can be said to have originated at the dawn of computing in the 1960s, when time-sharing was used for mainframe users to separate software from the physical host system. A virtual machine was defined in the early 1970s as "an efficient, isolated duplicate of a real computer machine."

Virtual machines as we know them today gained popularity over the past 20 years as companies embraced server virtualization to use the processing power of physical servers more efficiently, reducing their number and saving space in the data center. Since applications with different system requirements could be run on a single physical host, no different server hardware was required for each application.

How do virtual machines work?

In general, there are two types of virtual machines: process virtual machines, which spin up a single process, and system virtual machines, which offer full separation of the operating system and applications from the physical computer. Examples of process virtual machines include the Java Virtual Machine, the .NET Framework and the Parrot virtual machine. System virtual machines rely on hypervisors as intermediaries that give software access to hardware resources. A hypervisor emulates a computer's CPU, memory, hard drive, network and other hardware resources, creating a pool of resources that can be allocated to individual virtual machines according to their specific requirements. Hypervisor can support multiple virtual hardware platforms that are isolated from each other, allowing virtual machines to run Linux and Windows Server operating systems on the same physical host.

Well-known hypervisor vendors include VMware (ESX/ESXi), Intel/Linux Foundation (Xen), Oracle (MV Server for SPARC and Oracle VM Server for x86) and Microsoft (Hyper-V). Desktop systems can also use virtual machines. An example would be a Mac user running a virtual instance of Windows on his physical Mac hardware.

What are the two types of hypervisors?

The hypervisor manages and allocates resources to virtual machines. In addition, it plans and adjusts how resources are distributed based on the configuration of the hypervisor and virtual machines, and can reallocate resources when demand changes. Most hypervisors fall into one of two categories:

  • Type 1 - A bare-metal hypervisor runs directly on a physical host and has direct access to its hardware. Type-1 hypervisors typically run on servers and are considered more powerful and better performing than type-2 hypervisors, making them well suited for server, desktop and application virtualization. Examples of type 1 hypervisors include Microsoft Hyper-V and VMware ESXi.
  • Type 2 - Sometimes called a hosted hypervisor, a Type 2 hypervisor is installed on top of the host machine's operating system, which manages connections to hardware resources. Type 2 hypervisors are typically deployed on end-user systems for specific use cases. For example, a developer might use a Type 2 hypervisor to create a specific environment for building an application, or a data analyst might use it to test an application in an isolated environment. Examples include VMware Workstation and Oracle VirtualBox.

What are the advantages of virtual machines?

Because the software is separate from the physical host computer, users can run multiple instances of the operating system on a single piece of hardware, saving the company time, management costs and physical space. Another advantage is that VMs can support older applications, reducing or eliminating the need and cost of migrating an older application to an updated or different operating system. In addition, developers use VMs to test applications in a secure, sandboxed environment. Developers who want to see if their applications will run on a new operating system can use VMs to test software instead of buying new hardware and operating system in advance. For example, Microsoft recently updated its free Windows virtual machines, which allow developers to download an evaluation virtual machine running Windows 11 to try out the operating system without having to upgrade the main computer. This can also help isolate malware that might infect a particular VM instance. Since the software in the virtual machine can't manipulate the main computer, the malware can't spread as much damage.

What are the disadvantages of virtual machines?

Virtual machines have several drawbacks. Running multiple VMs on a single physical host can result in unstable performance, especially if the infrastructure requirements for the application are not met. This also makes them less efficient compared to a physical computer in many cases. In addition, if a physical server fails, all applications running on it will stop working. Most IT stores use a balance between physical and virtual systems.

What are other forms of virtualization?

The success of virtual machines in server virtualization has led to the application of virtualization in other areas, such as storage, networking and desktops. If a certain type of hardware is used in the data center, it is possible to virtualize it (such as application delivery controllers). In terms of network virtualization, companies are exploring network-as-a-service options and network functions virtualization (NFV), which uses commodity-class servers to replace specialized network equipment to enable more flexible and scalable services. This differs somewhat from software-defined networking, which separates the network control plane from the data forwarding plane to enable more automated policy-based provisioning and management of network resources. The third technology, virtual network functions, are software-based services that can run in an NFV environment, including processes such as routing, firewall, load balancing, WAN acceleration and encryption.

Verizon, for example, uses NFV to provide its virtual network services, which enable customers to launch new services and capabilities on demand. Services include virtual applications, routing, software-defined WANs, WAN optimization and even Session Border Controller as a Service (SBCaaS) for centrally managing and securely deploying IP-based real-time services such as VoIP and unified communications.

Virtual machines and containers

The development of virtual machines has led to the further development of technologies such as containers, which represent the next step in the development of this concept and are gaining recognition among web application developers. In a container environment, a single application with its dependencies can be virtualized. With much less imposition than a virtual machine, a container contains only binaries, libraries and applications. While some believe that container development can kill a VM, there are enough capabilities and benefits of VMs to keep the technology going. For example, VMs remain useful when running multiple applications together or when running legacy applications on older operating systems. Also, according to some, containers are less secure than VM hypervisors because containers have only one operating system that applications share, while VMs can isolate the application and operating system. Gary Chen, research manager at IDC's Software-Defined Compute division, said the virtual machine software market remains a foundational technology, even as customers explore cloud and container architectures. "The virtual machine software market has been remarkably resilient and will continue to grow positively over the next five years, despite being highly mature and approaching saturation," Chen writes in IDC's study "Worldwide Virtual Machine Software Forecast, 2019-2022."

Virtual machines, 5G and edge computing

Virtual machines are seen as part of new technologies such as 5G and edge computing. For example, virtual desktop infrastructure (VDI) providers such as Microsoft, VMware and Citrix are looking for ways to extend their VDI systems to employees who now work from home under a post-COVID hybrid model. "With VDI, you need extremely low latency, because you're sending your keystrokes and mouse movements to essentially a remote desktop," - says Mahadev Satyanarayanan, a professor of computer science at Carnegie Mellon University. In 2009, Satyanarayanan wrote about how virtual machine-based clouds could be used to provide better processing capabilities to mobile devices at the edge of the Internet, which led to the development of edge computing. In the 5G wireless space, the network slicing process uses software-defined networks and NFV technologies to help install network functionality on virtual machines on a virtualized server to provide services that used to run only on proprietary hardware. Like many of the technologies in use today, these emerging innovations would not have emerged if not for the original virtual machine concepts introduced decades ago.

źródło: https://www.computerworld.pl

Data protection

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/Data protection

Over the past few years, data security has become a priority topic among business owners. Through the development of technology, more and more sectors are being digitized, not only improving the operation of the company, but also exposing it to attacks from cyber criminals. We can't provide 100% protection for confidential information, but by putting the right steps in place, we can minimize the risk of a potential leak. As a result, both the company's good name and budget will not suffer. 

In an era that condones employees to use private devices for business purposes, security issues have never been so sensitive. Surveys show that only 40% of working people in Poland consider issues related to protecting the equipment they work on. This poses quite a challenge for business owners, who need to take care not only of the security of the data itself, but also to systematize regulations in relation to the surveillance of their subordinates' private devices. We need to realize the consequences that can accompany a data leak - even if we run a small or medium-sized company. Leakage of customers' private information, whether caused by the deliberate actions of external hackers or by an employee who took advantage of an unlucky open Wi-Fi network, can cost our company exorbitant amounts of money (leaving aside the risk of possible liability under, for example, data protection regulations). 

The potential threat may not only come from the network - it also applies to theft or damage to physical equipment. That's why we should make an effort to ensure that vital equipment for the operation of the company is properly secured, especially against the possibility of outside contact. In terms of data protection, establishing adequate oversight is much more crucial. The basis is choosing the right security system - one that is tailored to our company. It is at this stage that it is crucial to establish a data hierarchy, so that access to the most important information for the company, such as confidential customer data, will be reserved for those with authorizations - that is, employees for whom such knowledge is absolutely necessary to perform their duties. Let's also ask ourselves an important question - what will we do if somehow this data is lost? If we do not yet know the answer, let's think as soon as possible about separating a team whose task will be to periodically create backups and secure them properly. This way, in case of an attack and deletion of information or ordinary failure, we will be able to recover the data. The most perfect system will not work if it is not used by competent people. That's why measures to sensitize employees themselves to device security issues are so important. Let's start by making a list of tasks that all subordinates will have to perform before integrating their device into company operations, and another one describing cyclical procedures (such as updating or frequently changing passwords). Employees' knowledge will be based on this, while separate training and each time introducing new people to the company's security routine may be necessary to fully implement the security requirements. 

Like any professional solution, a surveillance system for confidential information first requires prudent planning. We do not have to deal with this ourselves - there are companies that professionally deal with helping companies implement security. However, we should remember to use common sense in this matter as well: when deciding on the services of specialists, be sure that they really are the best at what they do. In the age of the Internet, we can seek opinions on almost any service provider, and a good old recommendation by a friendly company will also work. Thanks to all these measures, we will be able to sleep peacefully, and our company - to function without unpleasant surprises. 

NVIDIA hits BIG in the Data Center market

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/NVIDIA hits BIG in the Data Center market

Nvidia is a company known for producing high-performance graphics cards and gaming hardware, but the company is also making waves in the data center space with its Nvidia Data Center platform. The platform offers a set of hardware and software products designed to accelerate data center workloads, from machine learning and AI to scientific computing and virtual desktop infrastructure.

NVIDIA'S Hardware

At the heart of the Nvidia Data Center platform is a line of data center GPUs, including the H100, A100, V100 and T4. These chips are optimized to accelerate a wide range of workloads, from training deep learning models to running virtual desktops. They offer high levels of parallelism and performance, and are designed to be scalable and meet the needs of large data centers. In addition to GPUs, Nvidia also offers a range of data center hardware products, including the DGX A100 system, which combines eight A100 GPUs with NVLink interconnect technology to deliver high performance computing and storage in a single server.

Software to manage

In addition to its hardware products, Nvidia also offers a suite of software products designed to help data center operators manage and optimize their workloads. This includes Nvidia GPU Cloud (NGC), which provides a repository of pre-trained deep learning models, as well as tools for deploying and managing GPU-accelerated workloads. Nvidia also offers a range of software tools for managing and optimizing GPU performance, including the Nvidia CUDA Toolkit, which provides a set of libraries and APIs for developing GPU-accelerated applications, and the Nvidia GPU Management Toolkit, which provides tools for monitoring and optimizing GPU performance in data center environments.

Purpose of the systems

The Nvidia Data Center platform is used in a wide range of industries and applications, from scientific computing and weather forecasting to financial services and healthcare. For example, the platform is used by the National Center for Atmospheric Research to perform high-resolution climate change simulations and by the Centers for Disease Control and Prevention to analyze genomic data to identify disease outbreaks. In the financial services industry, the Nvidia Data Center platform is used to run complex risk simulations and predictive analytics models, while in healthcare it is used to accelerate medical imaging and drug discovery research.

Summary

The Nvidia Data Center Platform offers a powerful set of hardware and software products designed to accelerate data center workloads across a wide range of industries and applications. With a focus on GPU acceleration and high-performance computing, the platform is well suited for machine learning and artificial intelligence workloads, as well as scientific computing and virtual desktop infrastructure. As data center workloads grow in complexity and scale, the Nvidia Data Center platform is likely to play an increasingly important role in accelerating data center performance and enabling new applications and use cases.

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